Multi-Area Stochastic Unit Commitment for High Wind

Report
Multi-Area Stochastic Unit Commitment for
High Wind Penetration in a Transmission
Constrained Network
Shmuel Oren
University of California , Berkeley
Joint work with Anthony Papavasiliou
Presented at
DIMACS Workshop on Energy Infrastructure
DIMACS Center, Rutgers University
February 20-22, 2013
Uncertainty
Negative Correlation with
Load
8000
250
7000
load
6000
150
5000
100
4000
50
0
load (MW)
wind power output (MW)
200
wind power
24
48
72
96
hour
120
144
168
3000
3
All Rights Reserved to Shmuel Oren
Conventional Solution
Source: CAISO
The DR Alternative to Expanding
Flexible Thermal Generation
Alternative DR Paradigms
Alternative Approaches to DR
Mobilization
Evaluation Methodology
• Comparison requires explicit accounting for uncertainty
for consistent determination of locational reserves.
• Stochastic unit commitment optimization accounts for
uncertainty by considering a limited number of
probabilistic wind and contingency scenarios, committing
slow reserves early with fast reserves and demand
response adjusted after uncertainties are revealed.
• Economic and reliability outcomes are calculated using
Monte Carlo simulation with large number of probabilistic
scenarios and contingencies
9
Model Structure
10
Unit Commitment
The Real Thing
Two Stage Stochastic Unit
Commitment
Scenario Selection
Decomposition
Parallelization
Scenario Selection
Wind Modeling and Data Sources
Model Calibration
Data Fit
WECC Case Study
Case Study Summary
Day Types
Competing Reserve Rules
Reserve Policy Comparison
Deep Integration, No Transmission, No Contingencies
Reserve Policy Comparison
No Wind
Reserve Policy Comparison
Moderate Integration
Reserve Policy Comparison
Deep Integration
Summary
Demand Response Study
Centralized Load Dispatch
Firm Demand Uncertainty
Market Based: Demand Side Bidding
Implementation of Coupling
Price and Wind Data For Coupling Model
Coupling Model (Smart Charging)
Dynamic Programming With
Recombinant Lattices
Demand Response Results
Conclusions
References
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Papavasiliou Anthony, Shmuel Oren and Richard O’Neill, “Reserve Requirements for Wind Power Integration:
A Scenario-Based Stochastic Programming Framework”, IEEE Transactions on Power System, Vol 26, No4
(2011), pp. 2197-2206
Papavasiliou A. and S. S. Oren, ”Integrating Renewable Energy Contracts and Wholesale Dynamic Pricing to
Serve Aggregate Flexible Loads” Invited Panel Paper, Proceeding of the IEEE PES GM, Detroit, Michigan, July
24-28, 2011.
Papavasiliou A. and S. S. Oren “Integration of Contracted Renewable Energy and Spot Market Supply to Serve
Flexible Loads”, Proceedings of the 18th World Congress of the International Federation of Automatic Control,
August 28 – September 2, 2011, Milano, Italy.
Papavasiliou A.and S. S. Oren, “Stochastic Modeling of Multi-area Wind Power Production “, Proceedings of
PMAPS 2012, Istanbul Turkey, June 10-14, 2012.
Oren S. S., Invited Panel Paper ” Renewable Energy Integration and the Impact of Carbon Regulation on the
Electric Grid “, Proceeding of the IEEE PES GM, San Diego CA, July 22-26, 2012.
Papavasiliou A., S. S. Oren, ” A Stochastic Unit Commitment Model for Integrating Renewable Supply and
Demand Response” Invited Panel Paper, Proceeding of the IEEE PES GM, San Diego, CA, July 24-28, 2012.
Papavasiliou A., S. S. Oren, “Large-Scale Integration of Deferrable Demand and Renewable Energy Sources in
Power Systems”, Accepted for publication in a special issue of the IEEE PES Transaction.
Papavasiliou A., S. S. Oren, “Multi-Area Stochastic Unit Commitment for High Wind Penetration in a
Transmission Constrained Network”, Accepted for publication in Journal of Operations Research.
Papavasiliou Anthony, Shmuel Oren, Barry Rountree “Applying High Performance Computing to Multi-Area
Stochastic Unit Commitment for Renewable Energy Integration”, Submitted to Mathematical Programming
(February 2013)
40
Questions?

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